Elevated Endogenous SDHA Drives Pathological Metabolism in Highly Metastatic Uveal Melanoma
Bibliographic record
Abstract
Purpose: Metastatic uveal melanoma (UM) has a very poor prognosis and no effective therapy. Despite remarkable advances in treatment of cutaneous melanoma, UM remains recalcitrant to chemotherapy, small-molecule kinase inhibitors, and immune-based therapy. Methods: We assessed two sets of oxidative phosphorylation (OxPhos) genes within 9858 tumors across 31 cancer types. An OxPhos inhibitor was used to characterize differential metabolic programming of highly metastatic monosomy 3 (M3) UM. Seahorse analysis and global metabolomics profiling were done to identify metabolic vulnerabilities. Analyses of UM TCGA data set were performed to determine expressions of key OxPhos effectors in M3 and non-M3 UM. We used targeted knockdown of succinate dehydrogenase A (SDHA) to determine the role of SDHA in M3 UM in conferring resistance to OxPhos inhibition. Results: We identified UM to have among the highest median OxPhos levels and showed that M3 UM exhibits a distinct metabolic profile. M3 UM shows markedly low succinate levels and has highly increased levels of SDHA, the enzyme that couples the tricarboxylic acid cycle with OxPhos by oxidizing (lowering) succinate. We showed that SDHA-high M3 UM have elevated expression of key OxPhos molecules, exhibit abundant mitochondrial reserve respiratory capacity, and are resistant to OxPhos antagonism, which can be reversed by SDHA knockdown. Conclusions: Our study has identified a critical metabolic program within poor prognostic M3 UM. In addition to the heightened mitochondrial functional capacity due to elevated SDHA, M3 UM SDHA-high mediate resistance to therapy that is reversible with targeted treatment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".